Triple

T16527964
Position Surface form Disambiguated ID Type / Status
Subject Rajkumar Santoshi E401487 entity
Predicate hasWorkedWith P9615 FINISHED
Object Ajay Devgn E632325 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Ajay Devgn | Statement: [Rajkumar Santoshi, hasWorkedWith, Ajay Devgn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ajay Devgn
Context triple: [Rajkumar Santoshi, hasWorkedWith, Ajay Devgn]
  • A. Ajay Devgn chosen
    Ajay Devgn is a prominent Indian film actor, director, and producer known for his intense performances in Hindi cinema and his versatility across action, drama, and comedy roles.
  • B. Akshaye Khanna
    Akshaye Khanna is an Indian film actor known for his versatile performances in Hindi cinema across both commercial hits and critically acclaimed dramas.
  • C. Sunny Deol
    Sunny Deol is an Indian film actor, director, and politician best known for his powerful action roles and intense performances in Hindi cinema.
  • D. Akshay Kumar
    Akshay Kumar is a prominent Indian film actor and producer, known for his action and comedy roles in Bollywood and his long-running, commercially successful career.
  • E. Salman Khan
    Salman Khan is an American educator and entrepreneur best known as the founder of the online learning platform Khan Academy.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d883838abc8190bc79cb2d41733ce2 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e32ed57be481908625d4c5aab0940c completed April 18, 2026, 7:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a018c32b4a88190a07db59965b38890 completed May 11, 2026, 7:58 a.m.
Created at: April 10, 2026, 5:14 a.m.